Applicability of the WHOQOL-BREF on early adolescence

The WHOQOL-BREF is one of the cross-cultural and widely used measures for assessing health-related quality of life (HRQOL). Previous studies of the HRQOL using the WHOQOL-BREF mainly focused on adult; however, there has been less work carried out on assessing the HRQOL on early adolescence. The goal of this study was to examine the applicability of the WHOQOL-BREF Taiwan version in early adolescent sample. A total of 365 junior high school students participated in this study. Participants completed the WHOQOL-BREF Taiwan version and five visual-analogue items on HRQOL evaluation. The results supported the originally designed four-factor model, and also indicated good item discrimination, internal reliability, factorial validity (by using confirmatory factor analysis) and construct validity (e.g., predictive validity, discriminant and convergent validity) after deleting two physical health items (i.e., “To what extent do you feel that your pain hinders you in doing what you need to do”; “Do you need medical treatment to cope with your daily life?”) and one social relationships item (i.e., “Are you satisfied with your sex life?”). Overall, this study provides the applicability of the WHOQOL-BREF Taiwan version in early adolescence. In addition, the WHOQOL-BREF Taiwan version may be of use to health professionals in the assessment and comparison of different age groups from early adolescence to adulthood.     

A multi-index model for quantile regression with ordinal data

In this paper, we propose a quantile approach to the multi-index semiparametric model for an ordinal response variable. Permitting non-parametric transformation of the response, the proposed method achieves a root-n rate of convergence and has attractive robustness properties. Further, the proposed model allows additional indices to model the remaining correlations between covariates and the residuals from the single-index, considerably reducing the error variance and thus leading to more efficient prediction intervals (PIs). The utility of the model is demonstrated by estimating PIs for functional status of the elderly based on data from the second longitudinal study of aging. It is shown that the proposed multi-index model provides significantly narrower PIs than competing models. Our approach can be applied to other areas in which the distribution of future observations must be predicted from ordinal response data.     

Encoding dissimilarity data for statistical model building

We summarize, review and comment upon three papers which discuss the use of discrete, noisy, incomplete, scattered pairwise dissimilarity data in statistical model building. Convex cone optimization codes are used to embed the objects into a Euclidean space which respects the dissimilarity information while controlling the dimension of the space. A “newbie” algorithm is provided for embedding new objects into this space. This allows the dissimilarity information to be incorporated into a smoothing spline ANOVA penalized likelihood model, a support vector machine, or any model that will admit reproducing kernel Hilbert space components, for nonparametric regression, supervised learning, or semisupervised learning. Future work and open questions are discussed. The papers are:     

Therapeutic Hypothermia: Quantification of the Transition of Core Body Temperature Using the Flexible Mixture Bent‐Cable Model for Longitudinal Data

Hypothermia which is induced by reducing core body temperature is a therapeutic tool used to prevent brain damage resulting from physical trauma. However, all physiological systems begin to slow down due to hypothermia and this can result in increased risk of mortality. Therefore quantification of the transition of core body temperature to early hypothermia is of great clinical interest. Conceptually core body temperature may exhibit an either gradual or abrupt transition. Bent‐cable regression is an appealing statistical tool to model such data due to the model's flexibility and readily interpretable regression coefficients. It handles more flexibly models that traditionally have been handled by low‐order polynomial models (for gradual transition) or piecewise linear changepoint models (for abrupt change). We consider a rat model to quantify the temporal trend of core body temperature primarily to address the question: What is the critical time point associated with a breakdown in the compensatory mechanisms following the start of hypothermia therapy? To this end, we develop a Bayesian modelling framework for bent‐cable regression of longitudinal data to simultaneously account for gradual and abrupt transitions. Our analysis reveals that: (i) about 39% of rats exhibit a gradual transition in core body temperature; (ii) the critical time point is approximately the same regardless of transition type; and (iii) both transition types show a significant increase of core body temperature followed by a significant decrease.